航线联盟下航空货运网络枢纽点选址问题研究

本文研究航空联盟下航空货运网络的枢纽点选址问题(HLP),基于枢纽点的数量及位置随机与容量的限制。首先引入航线联盟选择概率函数,确定不同航段上的航线自营运输或外包运输的概率;其次根据选址中心法则,以网络总成本最小化为目标,建立枢纽点选址模型;再次采用改进的免疫混沌遗传算法求解模型;最后,以顺丰航空公司案例进行实例分析。结果表明:1)本文改进的算法较免疫混沌遗传算法并与免疫遗传算法及CPLEX结果对比,发现本文设计的算法有较强的收敛性和计算速度,且计算结果与CPLEX求解器求解结果相差不大;2)枢纽点数量不确定时,枢纽点的位置多集中在东部城市;3)航空公司选择联盟环境可以大大降低运营成本,航空公司为提高自身利润,应考虑加入联盟,从而降低自身成本。     

基于线路“异质性”假设的轴辐式公共交通网络优化研究

特大城市公共交通局部静态拥堵问题日益成为制约公共交通网络运行效率提高的关键。针对这一问题改变线路“同质性”假设,在线路“异质性”假设的基础上,提出了将轴辐式网络设计运用到公共交通领域中来,综合考虑居民采用公共交通方式出行的单位运输可变成本、不变成本、枢纽换乘成本等要素,将枢纽间大型客车干线运输所带来的规模经济效应进行量化,构建了基于单分配、多枢纽、混合式网络结构特征的轴辐式公共交通网络优化模型,旨在多重约束下通过枢纽布局降低网络运输成本,提高公共交通网络站点的可达性。最后根据模拟退火算法对模型进行求解,并通过算例分析与讨论的方式验证了模型的有效性。     

轴辐式枢纽网络系统的关键枢纽设施识别问题研究

作为轴辐式枢纽网络关键因素的节点,尤其是起到中转作用的枢纽节点是网络稳定运行的重要环节。当这些节点被中断时,将对整个网络产生严重的影响。最直接的表现方式即是网络运行成本的急剧上升。因此本文研究如何识别对网络成本具有决定性影响的关键节点。首先,提出枢纽功能性中断问题和模型,并通过禁忌搜索算法进行求解。最后通过中国航空实例验证模型和算法在实际应用中的有效性。结果显示模型和算法能够有效识别出中国航空网络较重要的关键城市以及相对影响较弱的城市。可以为资源有限情况下,中国航空网络中各城市防御设施的合理分级和部署,为重点保护城市的鉴别提供依据和帮助。     

轴辐式同城快递网络模式研究

随着快递网点密度的稠密化,网络结构设计优劣直接关系到快递公司的运营成本和服务水平。针对快递公司的同城快递市场,在不改变现有网点规模选址的基础上改变网点的从属,结合轴辐式网络结构模式设计来提升其时效并优化成本和资源投入。以运输成本最小为目标,建立了带分支流向约束的枢纽选址模型,设计了高效的禁忌搜索算法对问题求解并验证了算法的有效性。最后提供相应的集散点选址分配解决方案,有利于整合资源形成规模效应,同时提供了同城快递分区管理依据,避免因网络结构复杂引起管理和运营混乱;从长远来看,有利于节约运营成本,增加其快递网络的柔性,降低运作管理的难度。     

基于随机Petri网的航空货运出港系统分析

航空货运出港作业是影响航空货运速度的重要环节。本文根据航空货运出港流程建立了出港系统的随机Petri网模型(SPN)和同构的马尔柯夫链(MC)。以国内某枢纽机场航空货站为例,计算了MC的稳定状态概率,分析了系统的运作效率和延时时间,并对提高航空货运出港系统运行效率提出了建议。     

考虑退货不确定性的多层次多站点逆向物流网络选址优化研究

在退货量不确定情况下,为追求电商企业逆向物流网络成本最小化,建立了多层次多站点的混合整数规划模型。将目标区域进行网格化处理,通过球上距离公式计算相邻备选站点、不同层次备选点间的运输距离,使用蒙特卡罗法模拟退货量,并设计了双染色体编码的遗传算法进行求解。算例验证了模型算法的可行性,并且得出了逆向物流网络成本最小时,快递站点和退货处理中心的选址,快递站点的选址与退货量大小存在对应关系,研究客户退货量会使物流网络选址得到优化。     

大规模定制模式下基于三角直觉模糊信息的生产指派问题研究

针对大规模定制模式下生产指派面临的模糊不确定性等问题,探讨如何运用三角直觉模糊数构建生产指派模型进而确定最满意的生产指派方案。首先,运用三角直觉模糊数刻画、设计基于顾客个性化需求与企业产出的相对偏差、产品价格与交货期等影响因素的顾客满意度函数和企业利润函数。其次,建立了兼顾企业利润和顾客满意度的调和函数,据此构建了生产指派模型,并证明该模型有可行解和最优解,然后说明模型的求解方法。最后,通过具体实例说明生产指派模型的求解过程及其有效性、合理性。     

机队运力配置和USApHMP问题的联合决策模型与算法

针对USApHMP (无容量限制的单分配枢纽网络设计)方法忽略了航空公司航线运力配置决策对单位客流量成本的影响问题,以枢纽机场选址、确定枢纽与非枢纽连接关系、航线机型及其频次选择为决策变量,综合考虑各城市对市场需求量、航线最大飞行频次、机队可用飞行时间等限制因素,以实现航线运力配置成本和枢纽设置成本最小化为目标函数,建立航线机型匹配及频次选择问题和USApHMP问题的联合决策优化模型,设计遗传算法进行求解.算例分析表明:考虑4种机型、10个城市和90个城市对的情况,与传统枢纽网络设计方法相比,联合决策模型的网络总成本降低了9.39%,且航线最大飞行频次是影响枢纽网络设计方案的重要因素.     

航空公司部分多属的枢纽机场定价研究

平台经济理论的运用是机场管理研究的新视角.以机场为平台商,航空公司和乘客为平台用户,在平台经济的分析框架下,以Armstrong价格模型为基础,并吸收Hotelling模型关于平台竞争及客户异质性的构建思想,针对竞争性的枢纽机场的定价策略进行研究.结果表明:机场的定价策略与航空公司和乘客的网络外部性参数和需求的价格弹性、乘客的预期交易次数、机场服务成本有关;倾斜的定价策略和航空收入与非航空收入的交叉补贴并不适用于模型假设下的机场.     

基于结构方程的我国风电企业国际化竞争力实证研究

对我国风电企业国际化发展竞争力进行了模型构建和实证研究,首先基于专家访谈调研与理论综合分析的基础上,构建了包括供应商、购买者、潜在进入者、同行业竞争者、替代品和企业自身六方面的我国风电企业国际化竞争力的模型指标框架;其次,运用信效度分析与验证性因子分析等方法对所构建的国际化竞争力指标体系的结构有效性进行了检验,并根据验证结果调整模型框架;接下来利用结构方程模型得到的路径系数获得了竞争力模型的权重,构建完成风电企业国际化竞争力评价模型;最后基于构建的国际化竞争力评价模型,对我国风电案例企业以及国际风电企业维斯塔斯、西门子歌美飒进行评价,计算得出的案例企业国际化竞争力水平与当前全球风电市场竞争格局和态势基本一致.     

Stochastic air freight hub location and flight routes planning

This paper introduced a stochastic programming model to address the air freight hub location and flight routes planning under seasonal demand variations. Most existing approaches to airline network design problems are restricted to a deterministic environment. However, the demand in the air freight market usually varies seasonally. The model is separated into two decision stages. The first stage, which is the decision not affected by randomness, determines the number and the location of hubs. The second stage, which is the decision affected by randomness, determines the flight routes to transport flows from origins to destinations based upon the hub location and realized uncertain scenario. Finally, the real data based on the air freight market in Taiwan and China is used to test the proposed model.     

A genetic algorithm for the problem of configuring a hub-and-spoke network for a LTL trucking company in Brazil

A heuristic based on genetic algorithms is proposed to the problem of configuring hub-and-spoke networks for trucking companies that operate less-than-truckload (LTL) services in Brazil. The problem consists of determining the number of consolidation terminals (also known as hubs), their locations and the assignment of the spokes to the hubs, aiming to minimize the total cost, which is composed of fixed and variable costs. The proposed formulation differs from similar formulations found in the literature in the sense that it allows variable scale-reduction factors for the transportation costs according to the total amount of freight between hub terminals, as occurs to less-than-truckload (LTL) freight carriers in Brazil. Our genetic algorithm approach incorporates an efficient local improvement procedure that is applied to each generated individual of the population. Computational results for benchmark problems are presented. A practical application to a real world problem involving one of the top-ten trucking companies in Brazil is also described.     

Design of intermodal logistics networks with hub delays

In an intermodal hub network, cost benefits can be achieved through the use of intermodal shipments and the economies of scale due to consolidation of flows at the hubs. However, due to limited resources at the logistics hubs, shipment delays may affect the service performance. In this research hub operations are modeled as a GI/G/1 queuing network and the shipments as multiple job classes with deterministic routings. By integrating the hub operation queuing model and the hub location-allocation model, the effect of limited hub resources on the design of intermodal logistics networks under service time requirements is investigated. The managerial insights gained from a study of 25-city road-rail intermodal logistics network show that the level of available hub resources significantly affects the logistics network structure in terms of number and location of hubs, total network costs, choice of single-hub and inter-hub shipments and service performance.     

A hub covering network design problem for cargo applications in Turkey

Hub location problems involve locating hub facilities and allocating demand nodes to hubs in order to provide service between origin–destination pairs. In this study, we focus on cargo applications of the hub location problem. Through observations from the Turkish cargo sector, we propose a new mathematical model for the hub location problem that relaxes the complete hub network assumption. Our model minimizes the cost of establishing hubs and hub links, while designing a network that services each origin–destination pair within a time bound. We formulate a single-allocation hub covering model that permits visiting at most three hubs on a route. The model is then applied to the realistic instances of the Turkish network and to the Civil Aeronautics Board data set.     

The hub location and network design problem with fixed and variable arc costs: formulation and dual-based solution heuristic

Many air, less-than-truck load and intermodal transportation and telecommunication networks incorporate hubs in an effort to reduce total cost. These hubs function as make bulk/break bulk or consolidation/deconsolidation centres. In this paper, a new hub location and network design formulation is presented that considers the fixed costs of establishing the hubs and the arcs in the network, and the variable costs associated with the demands on the arcs. The problem is formulated as a mixed integer programming problem embedding a multi-commodity flow model. The formulation can be transformed into some previously modelled hub network design problems. We develop a dual-based heuristic that exploits the multi-commodity flow problem structure embedded in the formulation. The test results indicate that the heuristic is an effective way to solve this computationally complex problem.     

The Tree of Hubs Location Problem

This paper presents the Tree of Hubs Location Problem. It is a network hub location problem with single assignment where a fixed number of hubs have to be located, with the particularity that it is required that the hubs are connected by means of a tree. The problem combines several aspects of location, network design and routing problems. Potential applications appear in telecommunications and transportation systems, when set-up costs for links between hubs are so high that full interconnection between hub nodes is prohibitive. We propose an integer programming formulation for the problem. Furthermore, we present some families of valid inequalities that reinforce the formulation and we give an exact separation procedure for them. Finally, we present computational results using the well-known AP and CAB data sets.     

A branch and cut algorithm for hub location problems with single assignment

The hub location problem with single assignment is the problem of locating hubs and assigning the terminal nodes to hubs in order to minimize the cost of hub installation and the cost of routing the traffic in the network. There may also be capacity restrictions on the amount of traffic that can transit by hubs. The aim of this paper is to investigate polyhedral properties of these problems and to develop a branch and cut algorithm based on these results.Acknowledgement The research of the first author was partially supported by the Banque Nationale de Belgique. The research of the second author was supported by France Telecom R&D under contract no. 99 1B 774. Their support is gratefully acknowledged.     

Location of hubs in a competitive environment

We offer a formulation that locates hubs on a network in a competitive environment; that is, customer capture is sought, which happens whenever the location of a new hub results in a reduction of the current cost (time, distance) needed by the traffic that goes from the specified origin to the specified destination. The formulation presented here reduces the number of variables and constraints as compared to existing covering models. This model is suited for both air passenger and cargo transportation. In this model, each origin–destination flow can go through either one or two hubs, and each demand point can be assigned to more than a hub, depending on the different destinations of its traffic. Links (“spokes”) have no capacity limit. Computational experience is provided.     

Hub and spoke network design with single-assignment,capacity decisions and balancing requirements

In this paper, an extension of the capacitated single-allocation hub location problem is considered in which the capacity of the hubs is part of the decision making process and balancing requirements are imposed on the network. The decisions to be made comprise (i) the selection of the hubs, (ii) the allocation of the spoke nodes to the hubs, (iii) the flow distribution through the sub network defined by the hubs and (iv) the capacity level at which each hub should operate. In the latter case, for each potential hub, a set of available capacities is considered among which one can be chosen. The objective is to minimize the total cost, which includes the setup cost for the hubs as well as the flow routing cost. Economies of scale are assumed for the costs. Balancing requirements are imposed to the network. In particular, a value is considered for the maximum difference between the maximum and minimum number of spoke nodes that are allocated to the hubs. Two mixed-integer linear programming formulations are proposed and analyzed for this problem. The results of a set of computational experiments using an off-the-shelf commercial solver are presented. These tests aim at evaluate the possibility of solving the problem to optimality using such a solver with a particular emphasis to the impact of the balancing requirements. The tests also allow an analysis of the gap of the bounds provided by linear relaxation.